AI Model2026
A Hugging Face model checkpoint that attaches a speculative decoding module to DeepSeek-V4-Flash, enabling million-token context handling with MoE architecture, FP4/FP8 mixed precision, and long-context inference optimizations.
AI Model2026
Detects and redacts personally identifiable information (PII) in user-typed text on-device, replacing sensitive values with stable placeholders before any data leaves the browser. Uses a small quantized ONNX token-classification model plus deterministic recognizers for structured identifiers, and applies a policy-driven keep-set for coarse geography.
AI Model2026
An uncensored GGUF build of GLM-5.2 that applies weight “abliteration” to remove refusal filters and produce a locally runnable text-generation model; includes quantization conversions and shard-merge instructions, intended for experimental research rather than production use.
AI Model2026
Performs zero-shot classification and regression on mixed numerical and categorical tabular data by treating training rows as in-context examples and predicting in a single forward pass. Uses alternating row/column attention and row compression; limited to 10 classes and model weights are non-commercial.
AI Model2026
Thinking-off fine-tune for coding-agent workflows that prioritizes fast next-step decisions, lower token usage and stable multi-turn tool calling. Highlights: MoE 35B base, MTP speculative decoding, SWE-bench 62.4% (300 cases). Best for local agent loops and automated debug cycles; requires disciplined harnessing and schema consistency.
AI Model2026
A large-scale MoE language model for agentic coding and long-context tasks, natively supporting 1M-token context and dynamically activating tens of billions of parameters per token. Uses sparse attention and zero-computation experts to allocate compute per-token; model weights planned for release.
AI Model2026
Provides GGUF/llama.cpp quantized variants of Qwen3.6-27B for local multimodal inference, tuned via online RL to cut average 'thinking' tokens by ≈50% while preserving answer quality; offers Q4_K_M/Q8_0/f16 builds and a separate mmproj for vision input.
AI Model2026
Provides quantized GGUF weights and configs for Agents‑A1 — a 35B Mixture-of-Experts agent trained for long-horizon, tool-enabled reasoning; supports 262K-context serving and runtimes like vLLM and SGLang.
AI Model2026
Diffusion-based generative model for scene and video synthesis, providing full Diffusers checkpoints and scene LoRA for fast adaptation. Includes Stage‑1 nano (1.3B) and pro (5B) variants and modular transformer/VAE components.
AI Model2026
A code-agent model for Lean 4 that automates repository-level formal proofs and verification; a Mixture-of-Experts architecture (119B total, 6.5B active) with 256k context, multimodal input and an Apache-2.0 license.
AI Model2026
Provides a large Mixture-of-Experts instruct LLM (295B total parameters, 21B active, 256K context) optimized for reasoning, long-context retention and agent workflows; open-sourced under Apache-2.0.
AI Model2026
Provides GGUF-quantized local-deploy weights for a 1B MiniCPM5-derived conversational LLM, embedding a 'thinking' chat template and supporting up to 128K-token context; ships Q4/Q5/Q8/F16 quant files (Q8_0 recommended) for llama.cpp, Ollama, and LM Studio.